Videos

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Data-Driven Multifidelity Methods for Monte Carlo Estimation and Beyond Thumbnail

Data-Driven Multifidelity Methods for Monte Carlo Estimation and Beyond

Presenter
  • Benjamin Peherstorfer
September 24, 2018
IPAM

Estimating Gap Junction Properties of Electrically Coupled Neurons From Measurements Made in the Soma

Presenter
  • Susan Cheng
August 7, 2018
MBI

A Combined Numerical, Mathematical, and Empirical Model to Predict the Evolution of Drug Resistance

Presenter
  • Julia Pelesko
August 6, 2018
MBI
Parameter uncertainty quantification using surrogate models applied to a spatial model of yeast mating polarization Thumbnail

Parameter uncertainty quantification using surrogate models applied to a spatial model of yeast mating polarization

Presenter
  • Ching-Shan Chou
May 29, 2018
IMA
Algorithms for accurately calculating forces between dipolar particles Thumbnail

Algorithms for accurately calculating forces between dipolar particles

Presenter
  • Sibani Biswal
March 15, 2018
IMA

Behavioral contagion type and its effect on disease dynamics

Presenter
  • Matthew Osborne
March 8, 2018
MBI
Representations of finite reductive groups: from characteristic zero to transverse characteristic Thumbnail

Representations of finite reductive groups: from characteristic zero to transverse characteristic

Presenter
  • Olivier Dudas
February 9, 2018
SLMath
Representations of finite reductive groups: from characteristic zero to transverse characteristic Thumbnail

Representations of finite reductive groups: from characteristic zero to transverse characteristic

Presenter
  • Olivier Dudas
February 8, 2018
SLMath
Representations of finite reductive groups: from characteristic zero to transverse characteristic Thumbnail

Representations of finite reductive groups: from characteristic zero to transverse characteristic

Presenter
  • Olivier Dudas
February 6, 2018
SLMath

New Progress on Stochastic Variance-Reduced Methods in Machine Learning: Adaptive Restart and Distributed Optimization

Presenter
  • Qihang Lin
December 12, 2017
IMA
Learning models: connections between boosting, hard-core distributions, dense models, GAN, and regularity II Thumbnail

Learning models: connections between boosting, hard-core distributions, dense models, GAN, and regularity II

Presenter
  • Russell Impagliazzo
November 14, 2017
IAS
Learning models: connections between boosting, hard-core distributions, dense models, GAN, and regularity I Thumbnail

Learning models: connections between boosting, hard-core distributions, dense models, GAN, and regularity I

Presenter
  • Russell Impagliazzo
November 13, 2017
IAS